Open AccessProceedings Article
Parallel structured duplicate detection
Rong Zhou,Eric A. Hansen +1 more
- 22 Jul 2007
- pp 1217-1223
TL;DR: It is shown that structured duplicate detection can also be used to reduce the number of slow synchronization operations needed in parallel graph search, and several techniques for integrating parallel and external-memory graph search in an efficient way are described.
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Abstract: We describe a novel approach to parallelizing graph search using structured duplicate detection. Structured duplicate detection was originally developed as an approach to external-memory graph search that reduces the number of expensive disk I/O operations needed to check stored nodes for duplicates, by using an abstraction of the search graph to localize memory references. In this paper, we show that this approach can also be used to reduce the number of slow synchronization operations needed in parallel graph search. In addition, we describe several techniques for integrating parallel and external-memory graph search in an efficient way. We demonstrate the effectiveness of these techniques in a graph-search algorithm for domain-independent STRIPS planning.
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Citations
•Proceedings Article
Best-first heuristic search for multi-core machines
Ethan Burns,Seth Lemons,Rong Zhou,Wheeler Ruml +3 more
- 11 Jul 2009
TL;DR: In an empirical comparison on STRIPS planning, grid pathfinding, and sliding tile puzzle problems using an 8-core machine, it is shown that A* implemented in this framework yields faster search than improved versions of previous parallel search proposals.
Linear-time disk-based implicit graph search
TL;DR: This work performs delayed duplicate detection without sorting, which runs in time linear in the number of nodes in practice, and performs the first complete breadth-first searches of the 2 × 7, 3 × 5, 4 × 4, and 2 ×× 8 sliding-tile Puzzles, verifying the radius of the 4 × 4 puzzle and determining theradius of the others.
78
Best-First Heuristic Search for Multicore Machines
TL;DR: In this article, the authors compare different approaches to parallel best-first search in a shared-memory setting, and present a new method, PBNF, that uses abstraction to partition the state space and to detect duplicate states without requiring frequent locking.
Best-first heuristic search for multicore machines
TL;DR: In this paper, the authors compare different approaches to parallel best-first search in a shared-memory setting, and present a new method, PBNF, that uses abstraction to partition the state space and to detect duplicate states without requiring frequent locking.
Evaluation of a simple, scalable, parallel best-first search strategy
TL;DR: Hash-Distributed A^@? (HDA^@?), a simple approach to parallel best-first search that asynchronously distributes and schedules work among processors based on a hash function of the search state, scales well, allowing the effective utilization of large amounts of distributed memory to optimally solve problems which require terabytes of RAM.
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References
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Breadth-first heuristic search
Rong Zhou,Eric A. Hansen +1 more
TL;DR: Optimal and approximate breadth-first heuristic search algorithms that use divide-and-conquer solution reconstruction and outperform other optimal and approximate heuristicsearch algorithms in solving domain-independent planning problems are described.
277
•Proceedings Article
Breadth-first heuristic search
Rong Zhou,Eric A. Hansen +1 more
- 02 Jun 2004
TL;DR: In this article, the authors describe optimal and approximate breadth-first heuristic search algorithms that use divide-and-conquer solution reconstruction for solving domain-independent planning problems and show that these algorithms outperform other optimal and approximation heuristics.
211
•Proceedings Article
Structured duplicate detection in external-memory graph search
Rong Zhou,Eric A. Hansen +1 more
- 25 Jul 2004
TL;DR: A new approach to duplicate detection in graph search is developed that localizes memory references by partitioning the search graph based on an abstraction of the state space, and expanding the frontier nodes of the graph in an order that respects this partition.
State of the art in parallel search techniques for discrete optimization problems
Ananth Grama,Vipin Kumar +1 more
TL;DR: The state of the art in parallel algorithms used for solving discrete optimization problems, including heuristic and nonheuristic techniques for searching graphs as well as trees, and speed-up anomalies in parallel search that are caused by the inherent speculative nature of search techniques are described.
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